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Citation Information
Cancer Treat Res Commun. 2018;14:1-6. doi: 10.1016/j.ctarc.2017.08.002. Epub 2017 Aug 19.
Diagnosis of lung tumor types based on metabolomic profiles in lymph node aspirates.
Sappington D, Helms S, Siegel E, Penney RB, Jeffus S, Bartter T, Bartter T, Boysen G.
Analytical methods | |||
|---|---|---|---|
| Comparative study | #1 | #2 | |
| Chromatography | LC | LC | |
| Ion source | ESI | ESI | |
| Positive/Negative mode | positive | positive | |
| Mass analyzer | QTOF | QTOF | |
| Identification level | MS/MS | MS/MS | |
Sample information | |||
|---|---|---|---|
| Comparative study | #1 | #2 | |
| Country | US | US | |
| Specimen | lymph node aspirates | lymph node aspirates | |
| Marker function | diagnosis | diagnosis | |
| Participants(Case) | Cancer type | adenocarcinoma, squamous cell carcinoma | adenocarcinoma |
| Stage | II, III, IV | II, III, IV | |
| Number | 50 | 31 | |
| Gender (M,F) | 31, 19 | 17, 14 | |
| Mean age (range) (M,F) | – | – | |
| Smoking status | – | – | |
| Participants(Control) | Type | non-malignant | squamous cell carcinoma |
| Number | 29.0 | 19.0 | |
| Gender (M,F) | 15, 14 | 14, 5 | |
| Mean age (range) (M,F) | – | – | |
| Smoking status | – | – | |
Data processing and metabolite identification | |
|---|---|
| Data processing software | MassHunter, MassProfilerProfessional |
| Database search | HMDB |
Statistics and concentration information | |
|---|---|
| Differential analysis method | OPLS-DA, PLS-DA |
| Classification method | – |
| Survival analysis method | – |
Metabolites identified in the paper
| Metabolite | Comparative study | Author-emphasized biomarkers | Mean concentration (case) | Mean concentration (control) | Fold change (case/control) | P-value | FDR | VIP |
|---|---|---|---|---|---|---|---|---|
| kynurenine | – | V | – | – | 0.97 | 0.92 | – | – |
| tryptophan | – | V | – | – | 0.98 | 0.92 | – | – |
| glutamate | – | V | – | – | 1.1 | 0.74 | – | – |
| glutamine | – | V | – | – | 0.92 | 0.7 | – | – |
| reduced glutathione | – | V | – | – | 1.54 | 0.57 | – | – |
| oxidized glutathione | – | V | – | – | 1.57 | 0.17 | – | – |
| kynurenine | – | V | – | – | 1.36 | 0.139 | – | – |
| glutamate | – | V | – | – | 1.44 | 0.045 | – | – |
| reduced glutathione | – | V | – | – | 4.62 | 0.043 | – | – |
| glutamine | – | V | – | – | 0.69 | 0.0076 | – | – |
| tryptophan | – | V | – | – | 0.59 | 0.0027 | – | – |
| oxidized glutathione | – | V | – | – | 2.53 | 0.0009 | – | – |
| Metabolite | Comparative study | Author-emphasized biomarkers | Cutoff value | AUROC (95%CI) | Sensitivity (%) | Specificity (%) | Accuracy (%) |
|---|---|---|---|---|---|---|---|
| kynurenine | – | V | – | – | – | – | – |
| tryptophan | – | V | – | – | – | – | – |
| glutamate | – | V | – | – | – | – | – |
| glutamine | – | V | – | – | – | – | – |
| reduced glutathione | – | V | – | – | – | – | – |
| oxidized glutathione | – | V | – | – | – | – | – |
| kynurenine | – | V | – | – | – | – | – |
| glutamate | – | V | – | – | – | – | – |
| reduced glutathione | – | V | – | – | – | – | – |
| glutamine | – | V | – | – | – | – | – |
| tryptophan | – | V | – | – | – | – | – |
| oxidized glutathione | – | V | – | – | – | – | – |
Paper graphical summary
